American Journal of Economics 2013, 3(5C): 177-183 DOI: 10.5923/c.economics.201301.30
A Structural Look at Service Loyalty:Role of Service Quality, Corporate Image, and Trust Farzana Quoquab* , Rohaida Basiruddin, Siti Zaleha Abdul Rasid International Business School, UniversitiTeknologi M alaysia, Kuala Lumpur, 54100, M alaysia
Abstract Th is study investigates the relationships among service loyalty, perceived service quality, corporate image, and
trust in the context of Malaysian mobile phone service market. Part ial least squares approach was used to analyze the survey data. Results suggest adequate predictive ability of the model and provide support for all hypothesized relationships. It is found that both perceived service quality and corporate image jointly build trust which eventually affects service loyalty. It is also evident that, perceived service quality directly as well as indirectly affects consumer trust.
Keywords Serv ice loyalty, Perceived service quality, Co rporate image, Trust, Malaysian mobile phone service market
1. Introduction Loyalty is often regarded as a Holy Grail for business firms due to its myriads of benefits[1],[2]. Past studies suggest that, loyalty contributes to increased amount of profit, enhances market share, generates positive word of mouth, and reduces customer switching tendency[3],[4]. However, creat ing customer loyalty is a daunting task, particularly in a highly co mpetitive business environment[5]. Most of the prior studies have identified satisfaction and quality as two prime antecedents of consumer loyalty[6],[7]. However, there is a need to incorporate other variables in the loyalty framework. The present research is such an effort to integrate service quality, corporate image, and trust in the service loyalty model. Unfortunately, the lin kages between service evaluation and service loyalty are often considered as a simple b ivariate relationship which certainly covers the true relat ionships[8]. Moreover, research pertaining to trust and image are predo minantly based on developed country context and litt le has been known related to the developing country perspective. It is argued that, models based on developed country settings may not be universally appropriate since cultural idiosyncratic characteristics may exhibit d ifferent relational strength and pattern across cultures and contexts[8],[9].Taken together, the present study aims to investigate the relationships among service loyalty, service quality, corporate image and trust in the context of mobile phone service usage. For the p resent study, mob ile phone serv ice sector is chosen as the research context. It is evident that mob ile * Corresponding author:
[email protected] (Farzana Quoquab) Published online at http://journal.sapub.org/economics Copyright © 2013 Scientific & Academic Publishing. All Rights Reserved
phone service is the fastest growing industry in the world[10]. However, in this industry, inducing other service provider’s customers to switch is a common practice[11]. This circu mstance not only affects service providers’ profit level, but also poses threat to service providers in making their customers loyal and to build a long term relat ionship. Another challenge to this industry is that, satisfied customers also switch due to the low (or absence of) switching barriers[12]. Therefore, indeed it is worthwh ile to understand what drives service loyalty in the context of mob ile phone service usage. The present research develops and extends existing conceptualizat ion of service dynamics by verify ing the med iating role of corporate image between perceived service quality and service loyalty. The present study is structured as follows. First, a brief literature review is presented related to the study constructs and hypotheses are developed. Next, the methodology is discussed and results are presented. Lastly, conclusion and imp licat ions are stated and limitations are acknowledged.
2. Literature Review and Development of Hypotheses It is often suggested that, retaining current customer is much more p rofitable than acquiring new customers since attracting new customers is five times more expensive than to retain the existing one[13].Considering its benefits, most of the firms consider loyalty as a panacea to many problems. It is important to note that, loyalty is more important for services than goods[14]. Intangibility of services makes the evaluation of service quality difficult which creates uncertainty to its customers and thus, loyalty acts as a risk reduction strategy for its customers[15]. For the present study, in indicating the loyalty construct,
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Farzana Quoquab et al.: A Structural Look at Service Loyalty:Role of Service Quality, Corporate Image, and Trust
the term service loyalty is used to differentiate it fro m goods loyalty. Due to the idiosyncratic nature of services and its unique features like perishability, intangibility, and inseparability, service loyalty greatly differs fro m goods based loyalty[14]. As such, the factors that contribute in explaining the service loyalty also varies fro m goods based loyalty. Being a prime co mpetit ive weapon in the service industry, service quality is often regarded as the key antecedent of service loyalty[16],[17]. It is the measure of consumers’ quality perception of service firms[18]. However, measuring service quality is far d ifficu lt than product’s quality[18]. Evaluating service quality heavily depends on evaluation of quality delivery process as well as its outcome[14],[18]. Past studies suggest that consumer’s favourable perception of service quality positively affect service loyalty[8],[19]. Moreover, it elevates consumer’s repeat purchase intention and enhances inclination to buy additional services fro m the same service provider, makes consumers less price sensitive and creates positive word-of-mouth[7],[17]. Usually, trust occurs when one party firmly believes that the act of other party will result in positive outcome[20]. As such, service quality may positively affect trust. Thus, it can be assumed that, when consumers would have positive perception toward the delivered service quality, it may create trust toward their service provider. In addition to this, when consumers trust any service provider, it reduces their level of risk which eventually creates service loyalty[21],[22]. In other words, when consumers trust a service provider, they tend to form a favourable purchasing intention towards that service provider[14]. In support of this view, it is found that trust is a significant p redictor of relational co mmit ment[23]. For a service firm, it is the hardest part to create trust among its customers and absence of trust is considered as the hardest obstacle for that firm[24]. However, some study contended that, corporate image can help in this regard, i.e., favourable corporate image contributes in creating consumer trust about the firm[25]. They have suggested that, in the financial services sector corporate image significantly and positively influence consumer trust in both traditional channels and over the internet. Therefore, it is also expected that, this relationship will substantiate in the context o f mob ile phone service as well. Corporate image is regarded as the overall imp ression that a person holds about a firm[26].As such, it is understood that, corporate image results from an evaluation process[27]. Th is evaluation derives fro m ideas, feelings and/or consumption experience that a consumer retrieves fro m h is or her memo ry wh ich eventually transforms into mental images[28]. As such, the impression of quality that is communicated by the service provider to its clients may affect corporate image[29]. In turn, image not only affects trust but also affects loyalty. As[30] pointed that corporate image is positively related to behavioural intention. Similarly,[29] also found support for this notion. They have
demonstrated that corporate image relates positively with customer loyalty in retailing and education sectors. Furthermore, in Danish postal services and Danish food retailing sector[31] and[32] found support of this relationship. In epito me, the present study simultaneously verifies the relationships among service loyalty (SL), perceived service quality (PSQ), corporate image (CI), and trust (TR). Based on the above discussions, follo wing hypotheses are formed : H1 :SQ will be positively related to SL H2 :TR will be positively related to SL H3 :CI will be positively related to SL H4 :SQ will be positively related to TR H5 :CI will be positively related to TR H6 :SQ will be positively related to CI H7 :TR will med iate the relat ionship between SQ and SL H8 : TR will mediate the relationship between CI and SL H9 :CI will mediate the relationshipbetween SQ and TR
3. Methodology 3.1. Measurement Measures for this study were adapted from past studies. In measuring service loyalty, loyalty scale was borrowed fro m[33],which was consisted of five items. Perceived service quality scale was borrowed fro m[34] for reason of data collection efficiency.In this study, perceived service quality is considered as a uni-dimensional construct as an overall evaluation of quality wh ich is in accordance with other researchers[11],[34]. This scale was co mprised of five items. On the other hand, corporate image scale was adapted fro m[35]. This scale contained five items. Lastly, to measure trust, a five-item scale was adapted from[11]. All study constructs were measured using a five-point Likert scale which ranged fro m “1=strongly disagree” to “5=strongly agree”. In this study, internal consistency reliability (measured by Cronbach’s coefficient alpha) for all constructs exceeded the suggested cut off value of 0.7 by[36] and ranged fro m 0.762 to 0.783. 3.2. Data Collection Data were collected by surveying a pool of students from a reputed private university in Malaysia. Using student as respondent is an old pract ice in marketing literature[19],[37]. Since the purpose of this study is to obtain theoretical generalizability over population generalizability, present study employed non-probability samp ling as the sampling technique[38],[39]. All together 300 questionnaires were distributed and 215 questionnaires were collected. After removing the outliers and incomplete questionnaires, 207 usable questionnaires were obtained. Among 207 respondents, 47% are male and the rest are female (53%) wh ich represents somewhat equal distribution. Most of the respondents’ age ranges from 18 – 27 years (86.6%) and the rest are ranged between 28 – 32 years (3.4%). In regard to ethnicity, 40.6% respondents are
American Journal of Economics 2013, 3(5C): 177-183
Chinese, 29.5% respondents are Malay, 42% are Indian and the rest are foreigner (9.6%). W ith respect to marital status, 91.3% respondents reported that they are single and majority of the respondent’s monthly income ranges fro m RM 500 to RM1000.
4. Results PLS approach was utilized to analy ze the data since predicting the relationship was the main concern, rather than theory testing[40],[41]. Smart PLS M3 Version 2.0 software was employed in this regard with the application of a bootstrapping technique to determine the significance levels for loadings, weights, and path coefficients. Following the general convention, a t wo step approach was considered to assess the conceptual model, i.e., the outer model (measurement model) and the inner model (structural model)[40],[41]. In the first stage, the outer model was assessed by evaluating psychometric properties of the measurement items. Next, the inner model was assessed to test the hypothesized relationships
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4.1. Measurement Model Confirmatory factor analysis (CFA) was carried out to test the measurement model. In this regard, reliability and validity were assessed. Convergent validity which is the degree to which observed variables are loaded on their underlying construct was assessed through factor loadings [40], co mposite reliab ility (CR) and average variance extracted (A VE)[42]. Convergent Validity As seen in Table 1, all items are loaded adequately on their underlying construct and exceeded the recommended cut-off value by[43] of 0.6. Additionally, CR values which represent the extent to which the construct indicators indicate the latent construct exceeded the suggested value of 0.7[62]. On the other hand, AVE which demonstrates the overall amount of variance in the indicators accounted for by the latent construct was above the recommended cut-off value of 0.5[42].
Table 1. Test results of convergent validity Construct
SL
TR
CI
PSQ
Measurement items
Loading
I will go on using this operator’s network service.
0.687
If I bought a new line, I would prefer this operator’s network service.
0.817
I recommend this SP to people.
0.769
I encourage friends regarding this SP who plans to subscribe to a mobile network service.
0.793
Even if the other operators’ billing is cheaper, I would go on using this operator’s network service. I trust this SP. I feel that I can rely on this SP to serve well. I trust the billing system.
0.608 0.608 0.809 0.783 0.734
I believe that I can trust this SP that it will not try to cheat me.
0.818
This SP is reliable because it is mainly concerned with the customer’s interests.
0.635 0.635
This SP is stable and firmly established. This SP is innovative and forward-looking. This SP has a social contribution for society.
0.714 0.721 0.736
This SP is a leading firm in the Malaysian telecommunications sector.
0.611
This SP has a positive image in the mind of consumers. The quality of the coverage area of my SP is satisfactory. This SP provides high quality customer support services.
0.803 0.630 0.785
I get adequate value added services (GPRS, WAP etc.) from this SP.
0.626
The pricing of the SP is reasonable. This SP’s offered services meet its advertisement promises.
0.766 0.822
CRa
AVEb
0.856
0.546
0.871
0.576
0.842
0.518
0.849
0.533
Note: SP refers to ‘service provider’. a Composite Reliability (CR) = (square of the summation of the factor loadings)/{(square of the summation of the factor loadings) + (square of the summation of the error variances)} b Average Variance Extract ed (AVE) = (summation of the square of the factor loadings)/{(summation of the square of the factor loadings) +(summation of the error variances)}
Farzana Quoquab et al.: A Structural Look at Service Loyalty:Role of Service Quality, Corporate Image, and Trust
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Discriminant Validity For the present study, discriminant valid ity at the construct level was assessed using[44] criterion. Conversely, as suggested by[40], item level d iscriminant validity was assessed by observing the cross loadings. The findings suggest that each of the measuring items for a particular latent construct was greater than its loadings on any other constructs. Next, criterion was assessed which reco mmends that the square-root of A VE for each construct is needed to be greater than other constructs’ correlation coefficient. Results provided in Table 2 demonstrate that all inter-construct correlation value were less than the value of square-root of A VE. Table 2. Assessment of discriminant validity at the construct level CL 0.739 0.448 0.295 0.308
CL TR PSQ CI
TR
PSQ
CI
0.759 0.392 0.215
0.720 0.243
0.730
Subsequently, perceived service quality (β = 0.238, p< 0.01) and Image (β = 0.122, p< 0.05) were positively and significantly related to trust. These results provide support for H4 and H5 . Additionally, the effect of perceived service quality was found to be a significant predictor of corporate image (β = 0.258, p< 0.01). Thus, H6 was supported. The results of the structural model are portrayed in Table 3. Mediation Effect Assessment In testing mediation effect, the Sobel test was performed to assess whether the indirect effect of the predictor variab le on the outcome variable through the mediator variable is significant. The results suggest that trust mediates the relationship between perceived service quality and service loyalty as well as between corporate image and service loyalty. To check whether these mediation effects are partial or full, the method from[45] was utilized and found that partial mediat ion exists in both cases and thus H7 and H8 are supported. Additionally, corporate image partially and significantly mediates the relationship between perceived service quality and trust wh ich provides support to accept H9 .
Note: Diagonals repres ent the square root of the AVE while the off-diagonal values represent the correl ations
Effect Size (f2) and Predictive Model Ability (Q2) Calculation
In a nutshell, all these test results depict that the measurement model adequately met the criteria of convergent and discriminant validity. Therefore, analysis proceeded to evaluate the structural model.
The effect of adding additional pred ictors in the model was assessed by calculating the effect size. If the value of f 2 is 0.02, it is considered as weak effect[46]. Moreover, the values of 0.15 and 0.35 are considered as moderate and substantial consequently. For the present study, f 2 values for adding each additional predictor were 0.156, 0.339, and 0.153 which demonstrate the existence of moderate effect size. The model capability to predict is another criterion that should be considered to assess the structural model (Hair et al., 2011). The model’s predictive ability is decided based on Stone-Geisser’s Q2 [47]. The value of Q2 was obtained by using a blindfolding procedure[42]. In this study, the predictive relevance values (Q2 ) for service loyalty, trust and corporate image were greater than zero which imp lies that the model has predictive relevance.
4.2. Structural Model Path coefficients were obtained using PLS algorith m. Additionally, bootstrapping technique was utilized to assess the level of significance of the structured paths. The results of bootstrapping indicated that all paths coefficients were significant at 0.01 and 0.05 levels. The R2 value was 0.385 suggesting that 38.5% of the variance in service loyalty can be exp lained by perceived service quality, trust and corporate image. Hypotheses testing Table 3. The results of the structural model Hypothesi s H1 H2 H3 H4 H5 H6 H7 H8 H9
Relationship PSQ → SL T R → SL CI → SL PSQ → TR CI → TR PSQ → CI PSQ→ T R → SL CI → TR → SL PSQ → CI → T R
Path coefficient 0.141 0.481 0.210 0.238 0.122 0. 258
t value
Result
2.631** 9.964** 3.290** 3.051** 2.003* 3.494** 3.392** 2.142* 2.440*
Supported Supported Supported Supported Supported Supported Supported Supported Supported
Note: **p
